Training details  

We use the same training hyper-parameters as [1]}. In particular, we are using softplus for GAN loss, and R1 regularization [2]} on both the sketch and image discriminator, \({D_Y}\)  and \({D_X}\) . We do not use path length regularization, as it has no effect on the latent mapping network. Also, we set the batch size to 4 for all of our experiments, except when the sketch inputs are less than four, where we set the batch size to 1.
